139,539 tools. Last updated 2026-05-26 11:46
"namespace:sh.xpay.mcp.price-sentinel" matching MCP tools:
- Recall Sentinel-2 NDVI (indices.ndvi, 10 m native) at a point or place. Composes locate → cell64 → recall in one call; auto-materializes on miss. When to use: Use when the user names a place (or lat/lng) and just wants the NDVI number. Polygon-resolved places default to a 16-cell fan-out aggregated as mean/median. Set `n_cells: 1` for point behaviour. For multi-band batches use emem_recall.Connector
- Per-band satellite-and-sensor fleet inventory — names the upstream platform (e.g. Sentinel-2A/B, MODIS Aqua/Terra, Landsat-8/9), revisit cadence, native resolution, and license for every materialized band. Lets an agent attribute imagery products correctly and pick the right band when revisit cadence matters. When to use: Call when the user asks 'which satellite is this from', 'what's the revisit time', or needs source attribution for a derived answer. Pair with emem_materializers for the wire path and emem_sources for the connector-level metadata.Connector
- True-colour Sentinel-2 L2A RGB thumbnail centred on a cell. PNG returned as a native MCP ImageContent block (mimeType image/png). Pure-Rust pipeline: STAC search + HTTP-Range COG reads + 2-98 percentile stretch + PNG encode. When to use: Call when the user wants a VISUAL of a place — 'show me what this looks like', 'before/after the flood', 'is there a forest here', 'is this developed'. Returns a 256×256 px RGB image (~2.56 km × ~2.56 km at S2's 10 m native resolution), centred on the cell. Pass `cell` as a cell64 string OR a place name (auto-resolved). `max_cloud` filters scenes by `eo:cloud_cover` (default 20 %); raise it (60–80 %) for cloud-prone tropics if you keep getting 'no scene' errors. `datetime` is an RFC 3339 interval like `"2024-01-01T00:00:00Z/2024-12-31T00:00:00Z"` for a temporal slice (defaults to last 90 days). `structuredContent` carries the STAC item id, capture time, cloud_cover, EPSG, and per-channel reflectance percentile stretch values used — quote those alongside the image so the receipt is reproducible.Connector
- Active grid encoding: cell64 ground resolution, lat/lng axis sizes, DGGS lineage. When to use: Call once at session start (or when the user asks about cell resolution / 'how big is a cell'). Returns the actual ground resolution today (~9.54 m × 9.55 m square at the equator (lat 21 bits × lng 22 bits, matching Sentinel-1/Sentinel-2 native pixel pitch). The cell64 bit layout reserves a resolution-tag field for future hierarchical refinement targeting H3-equivalent res-13 (~3.4 m) cells in v0.1.) and the spec target. Useful before you reason about whether one cell is enough or whether you need `emem_recall_polygon`.Connector
- Predict the next-vintage 128-D Tessera embedding at a cell using a small learned dynamics MLP. Reads the K=3 most-recent attested `geotessera.YYYY` vintages, runs them through an ONNX dynamics head (~200k params, CPU-fast), returns the predicted next-year embedding. The receipt's `model` block carries `model_id`, `version`, `blake2b_hex` (model_cid), training/validation provenance, and `honesty_warnings` flagging `untrained_baseline` when the artifact is the zero-init sentinel. Distinct from v1 (`emem_jepa_predict`) — v1 returns an NDVI scalar via closed-form coefficients; v2 returns a 128-D embedding from a learned model. When to use: Use when you want a forecast in EMBEDDING space rather than NDVI scalar — e.g. to find next-year analogs via `emem_find_similar` against the prediction, or to feed any algorithm in `algorithms_for_topic.foundation_embedding`. Returns 422 with a `/v1/backfill` hint when the cell has fewer than 3 consecutive Tessera vintages cached. Always read the receipt's `model.honesty_warnings` array — when it contains `untrained_baseline`, the prediction is the trivial 'predict last vintage' baseline (treat as no-op).Connector
- Single-shot free-text answer about a real-world location, backed by signed satellite/elevation/water/built-up receipts. Forwards a place mention plus a question; runs the locate → recall → algorithm chain server-side; returns one packaged envelope. When to use: Use when the question concerns a specific real-world place and a packaged, citation-bearing answer is preferable to manual primitive composition. Forward the user's question verbatim as `q` plus the location as `place` (free text), `cell` (cell64), or `lat`+`lng`. The server resolves the location, classifies the question to a topic, recalls every relevant band (auto-materializing Sentinel-2 / Sentinel-1 / Cop-DEM / JRC GSW / Overture / weather on miss), surfaces the algorithm recipes that compose those bands into named scores, and returns a single envelope with `topic_routing`, `facts`, `algorithms_for_question`, an optional Sentinel-2 RGB scene URL, and a `caveats` block (grid resolution, revisit cadence). All facts are signed by the responder; the receipt's `fact_cids` are content-addressed and citable. Set `include_image: true` to bundle the latest cloud-free Sentinel-2 thumbnail. Out-of-scope questions return `topic_routing.matched_topic: null` plus the full inventory so the caller can route elsewhere.Connector
Matching MCP Servers
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Matching MCP Connectors
Primary Purpose: Resolves real-time pricing, token-costs, and unit-efficiency for 500+ AI/SaaS providers. Key Capability: Normalizes disparate billing units (GPU Hours, Credits, 1M Tokens) into a standardized "Cost-per-Generation" metric. Context: Essential for agents performing "Cost-Benefit Analysis" or "Automated Model Switching." Accuracy: March 2026 Ground-Truth (Verified via Exa Semantic Search).
Find relevant security data from Sentinel data lake for building effective agents. More:aka.ms/s/de
- Scan an MCP server (URL or raw manifest JSON) against Helixar's Sentinel detection rules. Returns risk score, findings, and a Claude-generated security brief. Quick mode is free + authless (top 8 rules); deep mode runs all 26 rules with an api_key.Connector
- Entity relationship intelligence: finds all watchlist hits, traverses entity relation graph, screens connected entities, produces risk network map with composite scoring per node. Replaces 10-20 API calls + manual graph analysis. Costs $0.015 USDC via x402.Connector
- Know Your Agent — ERC-8004 registry lookup + sanctions screening + signed JWT attestation for any wallet address. Returns agent registration status, operator wallet, screening results, and coldStartSignals. FREE.Connector
- Cross-border transaction pre-screening: checks sender + receiver against watchlists, evaluates jurisdiction risk, provides forex corridor rate, returns PROCEED/REVIEW/FLAG/BLOCK recommendation. Replaces 6 API calls. Costs $0.008 USDC via x402.Connector
- Screen a blockchain wallet address against sanctioned/blacklisted crypto addresses (OFAC SDN, USDT Blacklist, USDC Blacklist, Ransomwhere, OpenSanctions, UK OFSI). Costs $0.003 USDC via x402.Connector
- Discover the supported Sentinel workflows and current model versions before scoring.Connector
- Fetch the least-cloudy Sentinel-2 L2A tile covering a given H3 cell from Microsoft Planetary Computer. Returns signed COG band URLs for all 6 Prithvi/Clay spectral bands (B02 Blue, B03 Green, B04 Red, B8A NIR, B11 SWIR1, B12 SWIR2), plus tile metadata. The tile is cached in memory for subsequent perception_classify or perception_embed calls.Connector
- Run Prithvi-EO-2.0-300M-TL-Sen1Floods11 flood classification on a Sentinel-2 tile previously fetched by perception_fetch_tile. Sends the 6-band chip to a RunPod endpoint and returns: dominant_class, flood_pixel_pct, confidence, class_counts, and the full perception_chain. The perception chain is written to Spatial Memory and a signed audit breadcrumb is dropped to the agent trail.Connector
- Get complete Mauritius economic pulse — ALL feeds in one call. Costs $0.005 USDC via x402.Connector
- Retrieve plan limits, monthly quota, remaining trial calls, and upgrade state for the current Sentinel API key.Connector
- Recall surface-water signals at a place: JRC Global Surface Water recurrence (1984–2021) + Sentinel-1 SAR backscatter (current). Pair detects standing water through clouds. When to use: Use when the user asks about flooding, wetlands, surface-water dynamics, or wants a robust water-presence check. JRC alone gives historical baseline; Sentinel-1 gives current flood detection.Connector
- Fetch required fields, optional fields, enums, and an example payload for a Sentinel workflow.Connector
- Get MUR exchange rates from Bank of Mauritius. Costs $0.001 USDC via x402.Connector
- Cross-border transaction pre-screening: checks sender + receiver against watchlists, evaluates jurisdiction risk, provides forex corridor rate, returns PROCEED/REVIEW/FLAG/BLOCK recommendation. Replaces 6 API calls. Costs $0.008 USDC via x402.Connector